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web_deep_search

Perform thorough web research by searching multiple search engines, extracting text from top pages, and reranking chunks to provide LLM-ready context for grounded answers.

Instructions

Deep search: search Bing+DDG → fetch top pages → extract text → rerank chunks → return LLM-ready context. Slower but thorough.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoLanguage codeen
queryYesSearch query
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided. The description discloses the multi-step pipeline and slower performance but lacks details on error handling, rate limits, or what happens if pages are inaccessible. Adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no wasted words. Front-loaded with the core purpose and ends with a clear trade-off warning. Ideal conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema or annotations, the description adequately explains the tool's function and trade-off. It lacks output format specifics but is complete enough for a search tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with two parameters (query, lang). The description does not add meaning beyond the schema; it only implicitly mentions the query. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool performs a deep search using Bing and DDG, fetches pages, extracts text, reranks chunks, and returns LLM-ready context. It clearly distinguishes from siblings like simpler search tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description notes 'Slower but thorough,' implying use when thoroughness is needed over speed. It does not explicitly name alternatives but provides clear context for when to choose this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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